Automotive Environment Sensing

 

Automotive environment sensors

Credits:

Contact hours: 28 lectures /28 lab

Assessment type: exam

Course coordinator: Tamás Bécsi, associate professor 

 

 

 

Instructors: 

Tamás Bécsi, PhD

Szilárd Aradi, PhD

Olivér Törő

 

Course Plan 2019 

Week

 

Lecture

Lab (Matlab exercises)

2019.02.06

1

Introduction (PDF)

A humble engineers guide to computational complexity

(and also the answer to when the World will end) (ZIP)

2019.02.13

2

Introduction to probabilistics

 Simple Robot with Bayes Rule discrete localization (TXT)

2019.02.20

3

Localization and Bayes Filtering

Particle Filter Localization, Bayes-KF estimation

2019.02.27

4

State Estimation,Kalman Filters, EKF

Various KF/EKF object tracking/state estimation examples

2019.03.06

5

SLAM

EKF SLAM problem

2019.03.13

6

Behavior

TBD

2019.03.20

 

Spring Break

 

 

7

Exam week

 

2019.04.03

8

Sensors Basics

TBD

2019.04.10

9

Faculty profession day

 

2019.04.17

10

Radar

FMCW example

2019.04.24

11

Ultrasonic/Lidar

Probabilistic Grid Mapping

2019.05.01

12

International Labor Day

 

2019.05.08

13

AI applications – connection to other topics

Scan matching

2019.05.15

14

Exam week